Name
Abstract | ||
|---|---|---|
In this paper, we present a new approach to build a more robust and efficient face recognition system. The idea is to fit the face recognition task into the new mathematical theory and algorithm of compressed sensing framework. With its beautiful theoretical results from compressed sensing, the new face recognition framework stably gives a better performance with some advantages compared to traditional approaches. Experimental results show the promising aspects of new approach when comparing with the most popular subspace analysis approaches in face recognition such as Eigenfaces, Fisherfaces, and Laplacianfaces in terms of recognition accuracy, efficiency, and numerical stability. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CIIP.2009.4937888 | CIIP |
Keywords | Field | DocType |
image coding,face recognition,subspace analysis,laplacianfaces,data compression,fisherfaces,compressed sensing,eigenfaces,accuracy,databases,numerical stability,face,principal component analysis | Computer vision,Facial recognition system,Eigenface,Subspace topology,Three-dimensional face recognition,Pattern recognition,Computer science,Mathematical theory,Artificial intelligence,Data compression,Numerical stability,Compressed sensing | Conference |
ISBN | Citations | PageRank |
978-1-4244-2760-4 | 1 | 0.36 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nhat Vo | 1 | 1 | 0.36 |
| Nhat Vo | 2 | 4 | 1.19 |
| Subhash Challa | 3 | 252 | 24.96 |
| Bill Moran | 4 | 141 | 23.49 |